Senior AI Data & Analytics Engineer II

Description

Who we are

The company (NYSE: IOT) is the pioneer of the Connected Operations Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At the company, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.

Working at the company means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.

About the role:

Want to build the data foundation powering AI and self-serve analytics at scale? As part of the company's Marketing Data and Analytics (MDA) Engineering team, you will shape the technical roadmap alongside our BI and Data Science peers. You will architect core Databricks pipelines, Gold Layer tables, and semantic models, turning ambitious, ambiguous business challenges into high-value data products, autonomous agents, and cross-functional automation.

This role is open to candidates residing in the US.

You should apply if:

You want to impact the industries that run our world: Your efforts will result in real-world impact – helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely.

You are the architect of your own career: If you put in the work, this role won’t be your last at the company. We set up our employees for success and have built a culture that encourages rapid career development, countless opportunities to experiment and master your craft in a hyper growth environment.

You’re energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers.

You want to be with the best: At the company, we win together, celebrate together and support each other. You will be surrounded by a high-calibre team that will encourage you to do your best.

In this role, you will:

Partner on defining the strategy and multi-quarter roadmap for MDA's data and AI foundation.

Architect and own the company's marketing data infrastructure: ETL/ELT pipelines, Databricks Gold Layer tables, and the core data models that power segmentation, targeting, automation, and analytics.

Design the semantic layers, data dictionaries, and structured documentation that enable self-serve BI and conversational analytics, partnering with the BI team to ensure core sales and marketing KPIs are built on trusted, well-modeled data.

Translate ambiguous business questions from Marketing, Sales, and R&D into clear requirements and scalable solutions, working autonomously without dedicated PM support and influencing decisions with data and sound reasoning.

Lead complex, cross-team initiatives end to end: stand up new data pipelines and integrations quickly, manage risk across interdependent teams, and own the reliability and data quality of what ships.

Serve as the senior technical lead for the team's hardest problems: raise the bar for engineering quality and code review, remove bottlenecks that slow multiple teams, and mentor engineers and analysts.

Drive the strategic use of AI to solve ambiguous, high-impact problems: build AI-enabled data products and agents, with the integrations, retrieval pipelines, and evaluation practices that keep them reliable and trustworthy.

Identify and automate manual workflows with AI across Marketing and GTM teams, taking ideas from concept to prototype to production and influencing org roadmaps.

Ship high-quality Python and SQL, increasingly by directing agentic coding tools, while holding a high bar for reviewing and verifying AI-generated work before it reaches production.

Champion, role model, and embed the company’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.

Minimum requirements for the role:

8+ years of experience in data engineering, analytics engineering, or AI engineering, including deep hands-on data engineering experience.

Expert-level Python and SQL, with strong hands-on data modeling and DBT experience.

Deep experience with data warehouse and lakehouse architectures, ETL/ELT, and the modern data stack, including hands-on Databricks (or similar, such as Snowflake or BigQuery).Experience building semantic layers and structured documentation optimized for AI ingestion and agentic workflows.Agentic coding tools (e.g., Claude Code, Cursor) are part of your regular workflow, and you verify and take ownership of AI-generated output.

Experience building, shipping, evaluating, and monitoring LLM or agent systems in production.

Track record of leading complex, cross-team data initiatives, including independent requirements gathering with technical and non-technical stakeholders.Experience supporting Marketing, Sales, or Product teams.

An ideal candidate also has:

Experience working with Databricks and building AI Agents within the ecosystem.

Software engineering background beyond data or AI engineering, with a track record of turning ambiguous, unfamiliar problems into well-architected, delivered solutions.

Expertise in data visualization and building dashboards for sales and marketing KPIs.

Familiarity with go-to-market data and systems: CRM (e.g., Salesforce), marketing automation, web analytics, and MarTech tools.

Experience building interactive applications with Streamlit, Claude workflows, or web frameworks.

Data science, machine learning, or predictive analytics experience.

Comfort working in an exploratory environment, testing and iterating on new data sources and methodologies.

The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below.

Annual Base Salary

$137,445 - $231,000 USD

Total Rewards

At the company, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time.

Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here.

Flexible Working

At the company, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.

Belonging at the company